Correlation Between MicroSectors FANG and KFA Mount
Can any of the company-specific risk be diversified away by investing in both MicroSectors FANG and KFA Mount at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining MicroSectors FANG and KFA Mount into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MicroSectors FANG Index and KFA Mount Lucas, you can compare the effects of market volatilities on MicroSectors FANG and KFA Mount and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in MicroSectors FANG with a short position of KFA Mount. Check out your portfolio center. Please also check ongoing floating volatility patterns of MicroSectors FANG and KFA Mount.
Diversification Opportunities for MicroSectors FANG and KFA Mount
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between MicroSectors and KFA is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding MicroSectors FANG Index and KFA Mount Lucas in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KFA Mount Lucas and MicroSectors FANG is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on MicroSectors FANG Index are associated (or correlated) with KFA Mount. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KFA Mount Lucas has no effect on the direction of MicroSectors FANG i.e., MicroSectors FANG and KFA Mount go up and down completely randomly.
Pair Corralation between MicroSectors FANG and KFA Mount
Given the investment horizon of 90 days MicroSectors FANG Index is expected to under-perform the KFA Mount. In addition to that, MicroSectors FANG is 7.68 times more volatile than KFA Mount Lucas. It trades about -0.11 of its total potential returns per unit of risk. KFA Mount Lucas is currently generating about -0.19 per unit of volatility. If you would invest 2,838 in KFA Mount Lucas on August 29, 2024 and sell it today you would lose (65.00) from holding KFA Mount Lucas or give up 2.29% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
MicroSectors FANG Index vs. KFA Mount Lucas
Performance |
| Timeline |
| MicroSectors FANG Index |
| KFA Mount Lucas |
MicroSectors FANG and KFA Mount Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with MicroSectors FANG and KFA Mount
The main advantage of trading using opposite MicroSectors FANG and KFA Mount positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MicroSectors FANG position performs unexpectedly, KFA Mount can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in KFA Mount will offset losses from the drop in KFA Mount's long position.| MicroSectors FANG vs. MicroSectors FANG Index | MicroSectors FANG vs. Direxion Daily Semiconductor | MicroSectors FANG vs. Direxion Daily Technology | MicroSectors FANG vs. Direxion Daily SP |
| KFA Mount vs. iMGP DBi Managed | KFA Mount vs. Simplify Exchange Traded | KFA Mount vs. Simplify Interest Rate | KFA Mount vs. AGFiQ Market Neutral |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.
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